Medical image registration and its application in retinal images: a review

Qiushi Nie, Xiaoqing Zhang, Yan Hu, Mingdao Gong, Jiang Liu

Research output: Journal PublicationReview articlepeer-review

Abstract

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities. Although several surveys have reviewed the development of medical image registration, they have not systematically summarized the existing medical image registration methods. To this end, a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives, aiming to help audiences quickly understand the development of medical image registration. In particular, we review recent advances in retinal image registration, which has not attracted much attention. In addition, current challenges in retinal image registration are discussed and insights and prospects for future research provided.

Original languageEnglish
Article number21
JournalVisual Computing for Industry, Biomedicine, and Art
Volume7
Issue number1
DOIs
Publication statusPublished - Dec 2024
Externally publishedYes

Keywords

  • Computer-aided diagnosis
  • Deep learning
  • Generative model
  • Medical image registration
  • Retina
  • Transformer

ASJC Scopus subject areas

  • Software
  • Computer Science (miscellaneous)
  • Medicine (miscellaneous)
  • Visual Arts and Performing Arts
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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